In network communication, how to ensure reliable and efficient data transmission in a network is always a research focus in the academic and industrial fields. Data transmission efficiency is directly related to network protocol performance. A throughput rate or transmission rate is one of important indicators for measuring the network protocol performance. In existing communications networks, the transmission control protocol (TCP) or the user datagram protocol (UDP) is generally used as a transport layer protocol. The TCP and the UDP are two most universal transport layer protocols of a TCP/IP model. According to statistics, currently more than 90% of global Internet data traffic is transmitted by using the TCP, whereas less than 10% of the global Internet data traffic is transmitted by using the UDP. Moreover, the proportion of the transmission by using TCP is still increasing continuously, and gradually, the TCP protocol even begins to be used to transmit multimedia data packets in multimedia applications that widely use the UDP protocol currently. However, the TCP transport protocol, that was designed more than twenty years ago, increasingly cannot meet requirements of rapidly developing high-speed network environment and new applications. For example, because of TCP mechanisms such as “double-window” congestion control or packet loss retransmission, when there is a packet loss or a delay in a network, a throughput rate of a TCP connection dramatically decreases, and bandwidth cannot be effectively used. Consequently, the TCP protocol cannot well support data transmission at a high throughput rate or transmission rate.
Aimed to overcome the TCP transmission rate problem, various network acceleration technologies emerge accordingly. These acceleration technologies may be basically classified into three types: a packet loss-based TCP acceleration technology, a delay-based TCP acceleration technology, and a learning-based TCP acceleration technology.
The loss-based TCP acceleration technology follows a mainstream manner in which by means of a packet loss, the TCP determines congestion and adjusts a transmission rate. Improvements of the loss-based TCP acceleration technology over a conventional TCP mainly lie in enlarging an initial congestion window (CNWD) and using a recovery manner more progressive than the conventional TCP to recover the CNWD after determining congestion by means of a packet loss, so as to reduce impact of the congestion on the rate. Although the improvements can really increase the rate in many situations, a packet loss may occur because of a non-congestion factor in many networks, especially in a wireless network. For example, a packet loss caused by a factor such as signal interference does not mean an occurrence of congestion. Therefore, in the loss-based TCP acceleration technology, using a packet loss as a congestion occurrence signal is very likely to cause mistakes. Consequently, the transmission rate is decreased, and bandwidth cannot be effectively used.
The delay-based TCP acceleration technology overcomes a main disadvantage of the loss-based TCP acceleration technology by using a delay change to determine a congestion degree and adjust a transmission rate accordingly. This mechanism is more in accordance with characteristics of a modern network, because a transmission rate can be lowered in time when stacking begins in a queue of a network node on which congestion occurs, so as to avoid worsening of the congestion and reduce or even avoid a packet loss. In addition, in the delay-based TCP acceleration technology, a packet loss is not considered as congestion, so as to maintain a relatively high rate when a non-congestion factor results in a packet loss. Therefore, compared with the loss-based TCP acceleration technology, the well-designed delay-based TCP acceleration technology has a significant improvement in the transmission rate. Even so, when a delay on a network path changes greatly, according to the delay-based TCP acceleration technology, a delay increase resulting from a non-congestion factor is incorrectly determined as congestion and congestion processing is performed. Consequently, an unnecessary reduction of the transmission rate is caused. For example, a delay of a wireless network including the mobile Internet changes frequently, and some network devices (especially security devices) may also sporadically introduce an extra delay in data packet processing.
The learning-based TCP acceleration technology uses a dynamic algorithm for network path feature self-learning. It observes and analyzes network features in real time based on every TCP connection, and adjusts the algorithm at any time according to the learned network features, so as to determine a congestion degree more accurately and determine a packet loss in a more timely manner, thereby processing congestion more properly and recovering a lost packet more quickly. In principle, this design overcomes a problem that a static algorithm cannot adapt to a network path feature change, and ensures that an acceleration effect remains effective in various different network environments with a frequently changed network delay and a frequently changed packet loss feature. However, in the learning-based TCP acceleration technology, a current network status needs to be learned by learning a historical record, and for a network with a random packet loss and large delay jitter, such learning/determining has no obvious advantage. Consequently, a network throughput rate/transmission rate is not significantly improved.
Summarizing the above, the throughput rate or transmission rate of an existing transport protocol still has large rooms for improvement. Although some acceleration algorithms may implement acceleration to an extent, a network development trend is that network traffic characteristics are more and more complex and unpredictable. Particularly, in a scenario of high delay, high packet loss rate, and high bandwidth-delay, network path feature continually changes. Therefore, an acceleration effect may be unstable, and adverse effects may even occur sometimes. Therefore, the throughput rate or transmission rate of a transport layer protocol in the prior art still needs to be improved.